code: def _fold_unfold_helper(draw, dim):
      stride = draw(
          st.one_of(
              st.lists(
                  st.integers(min_value=1, max_value=3),
                  min_size=dim,
                  max_size=dim,
              ),
              st.integers(min_value=1, max_value=3),
          )
      )
      padding = draw(
          st.one_of(
              st.integers(min_value=1, max_value=3),
              st.lists(
                  st.integers(min_value=1, max_value=2),
                  min_size=dim,
                  max_size=dim,
              ),
          )
      )
      dilation = draw(
          st.one_of(
              st.lists(
                  st.integers(min_value=1, max_value=3),
                  min_size=dim,
                  max_size=dim,
              ),
              st.integers(min_value=1, max_value=3),
          )
      )
      kernel_size = draw(
          st.one_of(
              st.integers(min_value=1, max_value=5),
              helpers.get_shape(
                  min_num_dims=dim,
                  max_num_dims=dim,
                  min_dim_size=1,
                  max_dim_size=5,
              ),
          )
      )
      return stride, padding, dilation, kernel_size
  
file_path: ivy/ivy_tests/test_ivy/test_frontends/test_torch/test_nn/test_functional/test_convolution_functions.py
imports: import math
  from hypothesis import strategies, assume
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
  from ivy_tests.test_ivy.test_functional.test_nn.test_layers import _assume_tf_dilation_gt_1
label_desc: Use image node_id 2 for calling a global function with example usage: _fold_unfold_helper(draw, dim) and returns: stride,  padding,  dilation,  kernel_size